Echo detection involves the creation of an acoustic signal, and detecting the acoustic echo reflected back. The reflected acoustic signal (called the “echo signal” or “echo”) is converted into an electrical signal, which may then be processed to extract information. One common application of echo detection is object and position detection. For instance, advanced vehicles often use echo detection to obtain information regarding positioning of objects external to the vehicle. For instance, echo detection may be used to inform a driver who is backing a vehicle up that there is an object behind the vehicle, thereby avoiding harm to the object, or to the external object. This is critical as the object detection works regardless of whether the object is inanimate, an animal, or even a person. Echo detection may also be used to facilitate automatic parking assistance.
Echo detection has been in use for some time. A ceramic resonator is the typical element that is used to both transmit and receive acoustic signals. Specifically, the transmission channel will first use the resonator to generate the acoustic signal. Then the receive channel will use the resonator to detect any reflections of that acoustic signal.
In one conventional implementation, the echo detection is accomplished by having the ceramic resonator generate an electrical signal that corresponds to the sensed acoustic pressures. The electrical signal is then passed through a Low Noise Amplifier (LNA) amplifier, and then through a high quality band pass filter. The filter serves to allow the echo signal to pass, while filtering out much of the unwanted amount noise caused by ambient acoustics in the environment. This unwanted noise can even saturate some of the downstream circuitry. Basically, the conventional approach is based on the direct comparison of the amplified echo envelope with a threshold level via the analog comparator.
The signal may then be passed through a variable gain amplifier in preparation for being provided to an Analog to Digital Converter (ADC). Thus, the acoustic signal or a derivative thereof is converted into a digital signal. The digital signal is then processed to determine whether or not the acoustic signal is truly representative of an echo received from the originally transmitted signal. Conventionally, this may be accomplished using a discrete Fourier transform (DFT) function employing a flat or more complex frequency shaping window. In the case of the flat window, the DFT selectivity is not precise due to its side band ripple. In the case of a more complex window (e.g. a Hann window), the side band ripple is significantly improved, but such a transform implementation is quite complicated and involves significant circuitry.